A Complete & Comprehensive Movie Review Dataset (CCMR)

Xuezhi Cao, Weiyue Huang, Yong Yu

Abstract: Online review sites are widely used for various domains including movies and restaurants. These sites now have strong influences towards users during purchasing processes. There exist plenty of research works for review sites on various aspects, including item recommendation, user behavior analysis, etc. However, due to the lack of complete and comprehensive dataset, there are still problems that remain to be solved. Therefore, in this paper we assemble and publish such dataset (CCMR) for the community. CCMR outruns existing datasets in terms of completeness, comprehensiveness and scale. Besides describing the dataset and its collecting methodology, we also propose several potential research topics that are made possible by having this dataset. Such topics include: (i) a statistical approach to reduce the impacts from fake reviews and (ii) analyzing and modeling the influences of public opinions towards users during rating actions. We further conduct preliminary analysis and experiments for both directions to show that they are promising.